{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](http://osloyi5le.bkt.clouddn.com/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%B7%A5%E7%A8%8B%E5%B8%88banner.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 对有连续值特征的数据进行决策树分类(鸢尾花数据集)\n",
    ">同济大学张子豪 2019-5-13"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 0.import需要的工具库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn import preprocessing\n",
    "from sklearn import tree\n",
    "from sklearn.datasets import load_iris"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.加载数据，认识鸢尾花数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "iris = load_iris()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['DESCR', 'data', 'feature_names', 'filename', 'target', 'target_names']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5.1, 3.5, 1.4, 0.2],\n",
       "       [4.9, 3. , 1.4, 0.2],\n",
       "       [4.7, 3.2, 1.3, 0.2],\n",
       "       [4.6, 3.1, 1.5, 0.2],\n",
       "       [5. , 3.6, 1.4, 0.2],\n",
       "       [5.4, 3.9, 1.7, 0.4],\n",
       "       [4.6, 3.4, 1.4, 0.3],\n",
       "       [5. , 3.4, 1.5, 0.2],\n",
       "       [4.4, 2.9, 1.4, 0.2],\n",
       "       [4.9, 3.1, 1.5, 0.1],\n",
       "       [5.4, 3.7, 1.5, 0.2],\n",
       "       [4.8, 3.4, 1.6, 0.2],\n",
       "       [4.8, 3. , 1.4, 0.1],\n",
       "       [4.3, 3. , 1.1, 0.1],\n",
       "       [5.8, 4. , 1.2, 0.2],\n",
       "       [5.7, 4.4, 1.5, 0.4],\n",
       "       [5.4, 3.9, 1.3, 0.4],\n",
       "       [5.1, 3.5, 1.4, 0.3],\n",
       "       [5.7, 3.8, 1.7, 0.3],\n",
       "       [5.1, 3.8, 1.5, 0.3],\n",
       "       [5.4, 3.4, 1.7, 0.2],\n",
       "       [5.1, 3.7, 1.5, 0.4],\n",
       "       [4.6, 3.6, 1. , 0.2],\n",
       "       [5.1, 3.3, 1.7, 0.5],\n",
       "       [4.8, 3.4, 1.9, 0.2],\n",
       "       [5. , 3. , 1.6, 0.2],\n",
       "       [5. , 3.4, 1.6, 0.4],\n",
       "       [5.2, 3.5, 1.5, 0.2],\n",
       "       [5.2, 3.4, 1.4, 0.2],\n",
       "       [4.7, 3.2, 1.6, 0.2],\n",
       "       [4.8, 3.1, 1.6, 0.2],\n",
       "       [5.4, 3.4, 1.5, 0.4],\n",
       "       [5.2, 4.1, 1.5, 0.1],\n",
       "       [5.5, 4.2, 1.4, 0.2],\n",
       "       [4.9, 3.1, 1.5, 0.2],\n",
       "       [5. , 3.2, 1.2, 0.2],\n",
       "       [5.5, 3.5, 1.3, 0.2],\n",
       "       [4.9, 3.6, 1.4, 0.1],\n",
       "       [4.4, 3. , 1.3, 0.2],\n",
       "       [5.1, 3.4, 1.5, 0.2],\n",
       "       [5. , 3.5, 1.3, 0.3],\n",
       "       [4.5, 2.3, 1.3, 0.3],\n",
       "       [4.4, 3.2, 1.3, 0.2],\n",
       "       [5. , 3.5, 1.6, 0.6],\n",
       "       [5.1, 3.8, 1.9, 0.4],\n",
       "       [4.8, 3. , 1.4, 0.3],\n",
       "       [5.1, 3.8, 1.6, 0.2],\n",
       "       [4.6, 3.2, 1.4, 0.2],\n",
       "       [5.3, 3.7, 1.5, 0.2],\n",
       "       [5. , 3.3, 1.4, 0.2],\n",
       "       [7. , 3.2, 4.7, 1.4],\n",
       "       [6.4, 3.2, 4.5, 1.5],\n",
       "       [6.9, 3.1, 4.9, 1.5],\n",
       "       [5.5, 2.3, 4. , 1.3],\n",
       "       [6.5, 2.8, 4.6, 1.5],\n",
       "       [5.7, 2.8, 4.5, 1.3],\n",
       "       [6.3, 3.3, 4.7, 1.6],\n",
       "       [4.9, 2.4, 3.3, 1. ],\n",
       "       [6.6, 2.9, 4.6, 1.3],\n",
       "       [5.2, 2.7, 3.9, 1.4],\n",
       "       [5. , 2. , 3.5, 1. ],\n",
       "       [5.9, 3. , 4.2, 1.5],\n",
       "       [6. , 2.2, 4. , 1. ],\n",
       "       [6.1, 2.9, 4.7, 1.4],\n",
       "       [5.6, 2.9, 3.6, 1.3],\n",
       "       [6.7, 3.1, 4.4, 1.4],\n",
       "       [5.6, 3. , 4.5, 1.5],\n",
       "       [5.8, 2.7, 4.1, 1. ],\n",
       "       [6.2, 2.2, 4.5, 1.5],\n",
       "       [5.6, 2.5, 3.9, 1.1],\n",
       "       [5.9, 3.2, 4.8, 1.8],\n",
       "       [6.1, 2.8, 4. , 1.3],\n",
       "       [6.3, 2.5, 4.9, 1.5],\n",
       "       [6.1, 2.8, 4.7, 1.2],\n",
       "       [6.4, 2.9, 4.3, 1.3],\n",
       "       [6.6, 3. , 4.4, 1.4],\n",
       "       [6.8, 2.8, 4.8, 1.4],\n",
       "       [6.7, 3. , 5. , 1.7],\n",
       "       [6. , 2.9, 4.5, 1.5],\n",
       "       [5.7, 2.6, 3.5, 1. ],\n",
       "       [5.5, 2.4, 3.8, 1.1],\n",
       "       [5.5, 2.4, 3.7, 1. ],\n",
       "       [5.8, 2.7, 3.9, 1.2],\n",
       "       [6. , 2.7, 5.1, 1.6],\n",
       "       [5.4, 3. , 4.5, 1.5],\n",
       "       [6. , 3.4, 4.5, 1.6],\n",
       "       [6.7, 3.1, 4.7, 1.5],\n",
       "       [6.3, 2.3, 4.4, 1.3],\n",
       "       [5.6, 3. , 4.1, 1.3],\n",
       "       [5.5, 2.5, 4. , 1.3],\n",
       "       [5.5, 2.6, 4.4, 1.2],\n",
       "       [6.1, 3. , 4.6, 1.4],\n",
       "       [5.8, 2.6, 4. , 1.2],\n",
       "       [5. , 2.3, 3.3, 1. ],\n",
       "       [5.6, 2.7, 4.2, 1.3],\n",
       "       [5.7, 3. , 4.2, 1.2],\n",
       "       [5.7, 2.9, 4.2, 1.3],\n",
       "       [6.2, 2.9, 4.3, 1.3],\n",
       "       [5.1, 2.5, 3. , 1.1],\n",
       "       [5.7, 2.8, 4.1, 1.3],\n",
       "       [6.3, 3.3, 6. , 2.5],\n",
       "       [5.8, 2.7, 5.1, 1.9],\n",
       "       [7.1, 3. , 5.9, 2.1],\n",
       "       [6.3, 2.9, 5.6, 1.8],\n",
       "       [6.5, 3. , 5.8, 2.2],\n",
       "       [7.6, 3. , 6.6, 2.1],\n",
       "       [4.9, 2.5, 4.5, 1.7],\n",
       "       [7.3, 2.9, 6.3, 1.8],\n",
       "       [6.7, 2.5, 5.8, 1.8],\n",
       "       [7.2, 3.6, 6.1, 2.5],\n",
       "       [6.5, 3.2, 5.1, 2. ],\n",
       "       [6.4, 2.7, 5.3, 1.9],\n",
       "       [6.8, 3. , 5.5, 2.1],\n",
       "       [5.7, 2.5, 5. , 2. ],\n",
       "       [5.8, 2.8, 5.1, 2.4],\n",
       "       [6.4, 3.2, 5.3, 2.3],\n",
       "       [6.5, 3. , 5.5, 1.8],\n",
       "       [7.7, 3.8, 6.7, 2.2],\n",
       "       [7.7, 2.6, 6.9, 2.3],\n",
       "       [6. , 2.2, 5. , 1.5],\n",
       "       [6.9, 3.2, 5.7, 2.3],\n",
       "       [5.6, 2.8, 4.9, 2. ],\n",
       "       [7.7, 2.8, 6.7, 2. ],\n",
       "       [6.3, 2.7, 4.9, 1.8],\n",
       "       [6.7, 3.3, 5.7, 2.1],\n",
       "       [7.2, 3.2, 6. , 1.8],\n",
       "       [6.2, 2.8, 4.8, 1.8],\n",
       "       [6.1, 3. , 4.9, 1.8],\n",
       "       [6.4, 2.8, 5.6, 2.1],\n",
       "       [7.2, 3. , 5.8, 1.6],\n",
       "       [7.4, 2.8, 6.1, 1.9],\n",
       "       [7.9, 3.8, 6.4, 2. ],\n",
       "       [6.4, 2.8, 5.6, 2.2],\n",
       "       [6.3, 2.8, 5.1, 1.5],\n",
       "       [6.1, 2.6, 5.6, 1.4],\n",
       "       [7.7, 3. , 6.1, 2.3],\n",
       "       [6.3, 3.4, 5.6, 2.4],\n",
       "       [6.4, 3.1, 5.5, 1.8],\n",
       "       [6. , 3. , 4.8, 1.8],\n",
       "       [6.9, 3.1, 5.4, 2.1],\n",
       "       [6.7, 3.1, 5.6, 2.4],\n",
       "       [6.9, 3.1, 5.1, 2.3],\n",
       "       [5.8, 2.7, 5.1, 1.9],\n",
       "       [6.8, 3.2, 5.9, 2.3],\n",
       "       [6.7, 3.3, 5.7, 2.5],\n",
       "       [6.7, 3. , 5.2, 2.3],\n",
       "       [6.3, 2.5, 5. , 1.9],\n",
       "       [6.5, 3. , 5.2, 2. ],\n",
       "       [6.2, 3.4, 5.4, 2.3],\n",
       "       [5.9, 3. , 5.1, 1.8]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.data #ndarray类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sepal length (cm)',\n",
       " 'sepal width (cm)',\n",
       " 'petal length (cm)',\n",
       " 'petal width (cm)']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.feature_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['setosa', 'versicolor', 'virginica'], dtype='<U10')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.target_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/opt/conda/lib/python3.5/site-packages/sklearn/datasets/data/iris.csv'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.filename"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".. _iris_dataset:\n",
      "\n",
      "Iris plants dataset\n",
      "--------------------\n",
      "\n",
      "**Data Set Characteristics:**\n",
      "\n",
      "    :Number of Instances: 150 (50 in each of three classes)\n",
      "    :Number of Attributes: 4 numeric, predictive attributes and the class\n",
      "    :Attribute Information:\n",
      "        - sepal length in cm\n",
      "        - sepal width in cm\n",
      "        - petal length in cm\n",
      "        - petal width in cm\n",
      "        - class:\n",
      "                - Iris-Setosa\n",
      "                - Iris-Versicolour\n",
      "                - Iris-Virginica\n",
      "                \n",
      "    :Summary Statistics:\n",
      "\n",
      "    ============== ==== ==== ======= ===== ====================\n",
      "                    Min  Max   Mean    SD   Class Correlation\n",
      "    ============== ==== ==== ======= ===== ====================\n",
      "    sepal length:   4.3  7.9   5.84   0.83    0.7826\n",
      "    sepal width:    2.0  4.4   3.05   0.43   -0.4194\n",
      "    petal length:   1.0  6.9   3.76   1.76    0.9490  (high!)\n",
      "    petal width:    0.1  2.5   1.20   0.76    0.9565  (high!)\n",
      "    ============== ==== ==== ======= ===== ====================\n",
      "\n",
      "    :Missing Attribute Values: None\n",
      "    :Class Distribution: 33.3% for each of 3 classes.\n",
      "    :Creator: R.A. Fisher\n",
      "    :Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)\n",
      "    :Date: July, 1988\n",
      "\n",
      "The famous Iris database, first used by Sir R.A. Fisher. The dataset is taken\n",
      "from Fisher's paper. Note that it's the same as in R, but not as in the UCI\n",
      "Machine Learning Repository, which has two wrong data points.\n",
      "\n",
      "This is perhaps the best known database to be found in the\n",
      "pattern recognition literature.  Fisher's paper is a classic in the field and\n",
      "is referenced frequently to this day.  (See Duda & Hart, for example.)  The\n",
      "data set contains 3 classes of 50 instances each, where each class refers to a\n",
      "type of iris plant.  One class is linearly separable from the other 2; the\n",
      "latter are NOT linearly separable from each other.\n",
      "\n",
      ".. topic:: References\n",
      "\n",
      "   - Fisher, R.A. \"The use of multiple measurements in taxonomic problems\"\n",
      "     Annual Eugenics, 7, Part II, 179-188 (1936); also in \"Contributions to\n",
      "     Mathematical Statistics\" (John Wiley, NY, 1950).\n",
      "   - Duda, R.O., & Hart, P.E. (1973) Pattern Classification and Scene Analysis.\n",
      "     (Q327.D83) John Wiley & Sons.  ISBN 0-471-22361-1.  See page 218.\n",
      "   - Dasarathy, B.V. (1980) \"Nosing Around the Neighborhood: A New System\n",
      "     Structure and Classification Rule for Recognition in Partially Exposed\n",
      "     Environments\".  IEEE Transactions on Pattern Analysis and Machine\n",
      "     Intelligence, Vol. PAMI-2, No. 1, 67-71.\n",
      "   - Gates, G.W. (1972) \"The Reduced Nearest Neighbor Rule\".  IEEE Transactions\n",
      "     on Information Theory, May 1972, 431-433.\n",
      "   - See also: 1988 MLC Proceedings, 54-64.  Cheeseman et al\"s AUTOCLASS II\n",
      "     conceptual clustering system finds 3 classes in the data.\n",
      "   - Many, many more ...\n"
     ]
    }
   ],
   "source": [
    "print(iris.DESCR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "iris_feature_name = iris.feature_names\n",
    "iris_features = iris.data\n",
    "iris_target_name = iris.target_names\n",
    "iris_target = iris.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sepal length (cm)',\n",
       " 'sepal width (cm)',\n",
       " 'petal length (cm)',\n",
       " 'petal width (cm)']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_feature_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5.1, 3.5, 1.4, 0.2],\n",
       "       [4.9, 3. , 1.4, 0.2],\n",
       "       [4.7, 3.2, 1.3, 0.2],\n",
       "       [4.6, 3.1, 1.5, 0.2],\n",
       "       [5. , 3.6, 1.4, 0.2],\n",
       "       [5.4, 3.9, 1.7, 0.4],\n",
       "       [4.6, 3.4, 1.4, 0.3],\n",
       "       [5. , 3.4, 1.5, 0.2],\n",
       "       [4.4, 2.9, 1.4, 0.2],\n",
       "       [4.9, 3.1, 1.5, 0.1],\n",
       "       [5.4, 3.7, 1.5, 0.2],\n",
       "       [4.8, 3.4, 1.6, 0.2],\n",
       "       [4.8, 3. , 1.4, 0.1],\n",
       "       [4.3, 3. , 1.1, 0.1],\n",
       "       [5.8, 4. , 1.2, 0.2],\n",
       "       [5.7, 4.4, 1.5, 0.4],\n",
       "       [5.4, 3.9, 1.3, 0.4],\n",
       "       [5.1, 3.5, 1.4, 0.3],\n",
       "       [5.7, 3.8, 1.7, 0.3],\n",
       "       [5.1, 3.8, 1.5, 0.3],\n",
       "       [5.4, 3.4, 1.7, 0.2],\n",
       "       [5.1, 3.7, 1.5, 0.4],\n",
       "       [4.6, 3.6, 1. , 0.2],\n",
       "       [5.1, 3.3, 1.7, 0.5],\n",
       "       [4.8, 3.4, 1.9, 0.2],\n",
       "       [5. , 3. , 1.6, 0.2],\n",
       "       [5. , 3.4, 1.6, 0.4],\n",
       "       [5.2, 3.5, 1.5, 0.2],\n",
       "       [5.2, 3.4, 1.4, 0.2],\n",
       "       [4.7, 3.2, 1.6, 0.2],\n",
       "       [4.8, 3.1, 1.6, 0.2],\n",
       "       [5.4, 3.4, 1.5, 0.4],\n",
       "       [5.2, 4.1, 1.5, 0.1],\n",
       "       [5.5, 4.2, 1.4, 0.2],\n",
       "       [4.9, 3.1, 1.5, 0.2],\n",
       "       [5. , 3.2, 1.2, 0.2],\n",
       "       [5.5, 3.5, 1.3, 0.2],\n",
       "       [4.9, 3.6, 1.4, 0.1],\n",
       "       [4.4, 3. , 1.3, 0.2],\n",
       "       [5.1, 3.4, 1.5, 0.2],\n",
       "       [5. , 3.5, 1.3, 0.3],\n",
       "       [4.5, 2.3, 1.3, 0.3],\n",
       "       [4.4, 3.2, 1.3, 0.2],\n",
       "       [5. , 3.5, 1.6, 0.6],\n",
       "       [5.1, 3.8, 1.9, 0.4],\n",
       "       [4.8, 3. , 1.4, 0.3],\n",
       "       [5.1, 3.8, 1.6, 0.2],\n",
       "       [4.6, 3.2, 1.4, 0.2],\n",
       "       [5.3, 3.7, 1.5, 0.2],\n",
       "       [5. , 3.3, 1.4, 0.2],\n",
       "       [7. , 3.2, 4.7, 1.4],\n",
       "       [6.4, 3.2, 4.5, 1.5],\n",
       "       [6.9, 3.1, 4.9, 1.5],\n",
       "       [5.5, 2.3, 4. , 1.3],\n",
       "       [6.5, 2.8, 4.6, 1.5],\n",
       "       [5.7, 2.8, 4.5, 1.3],\n",
       "       [6.3, 3.3, 4.7, 1.6],\n",
       "       [4.9, 2.4, 3.3, 1. ],\n",
       "       [6.6, 2.9, 4.6, 1.3],\n",
       "       [5.2, 2.7, 3.9, 1.4],\n",
       "       [5. , 2. , 3.5, 1. ],\n",
       "       [5.9, 3. , 4.2, 1.5],\n",
       "       [6. , 2.2, 4. , 1. ],\n",
       "       [6.1, 2.9, 4.7, 1.4],\n",
       "       [5.6, 2.9, 3.6, 1.3],\n",
       "       [6.7, 3.1, 4.4, 1.4],\n",
       "       [5.6, 3. , 4.5, 1.5],\n",
       "       [5.8, 2.7, 4.1, 1. ],\n",
       "       [6.2, 2.2, 4.5, 1.5],\n",
       "       [5.6, 2.5, 3.9, 1.1],\n",
       "       [5.9, 3.2, 4.8, 1.8],\n",
       "       [6.1, 2.8, 4. , 1.3],\n",
       "       [6.3, 2.5, 4.9, 1.5],\n",
       "       [6.1, 2.8, 4.7, 1.2],\n",
       "       [6.4, 2.9, 4.3, 1.3],\n",
       "       [6.6, 3. , 4.4, 1.4],\n",
       "       [6.8, 2.8, 4.8, 1.4],\n",
       "       [6.7, 3. , 5. , 1.7],\n",
       "       [6. , 2.9, 4.5, 1.5],\n",
       "       [5.7, 2.6, 3.5, 1. ],\n",
       "       [5.5, 2.4, 3.8, 1.1],\n",
       "       [5.5, 2.4, 3.7, 1. ],\n",
       "       [5.8, 2.7, 3.9, 1.2],\n",
       "       [6. , 2.7, 5.1, 1.6],\n",
       "       [5.4, 3. , 4.5, 1.5],\n",
       "       [6. , 3.4, 4.5, 1.6],\n",
       "       [6.7, 3.1, 4.7, 1.5],\n",
       "       [6.3, 2.3, 4.4, 1.3],\n",
       "       [5.6, 3. , 4.1, 1.3],\n",
       "       [5.5, 2.5, 4. , 1.3],\n",
       "       [5.5, 2.6, 4.4, 1.2],\n",
       "       [6.1, 3. , 4.6, 1.4],\n",
       "       [5.8, 2.6, 4. , 1.2],\n",
       "       [5. , 2.3, 3.3, 1. ],\n",
       "       [5.6, 2.7, 4.2, 1.3],\n",
       "       [5.7, 3. , 4.2, 1.2],\n",
       "       [5.7, 2.9, 4.2, 1.3],\n",
       "       [6.2, 2.9, 4.3, 1.3],\n",
       "       [5.1, 2.5, 3. , 1.1],\n",
       "       [5.7, 2.8, 4.1, 1.3],\n",
       "       [6.3, 3.3, 6. , 2.5],\n",
       "       [5.8, 2.7, 5.1, 1.9],\n",
       "       [7.1, 3. , 5.9, 2.1],\n",
       "       [6.3, 2.9, 5.6, 1.8],\n",
       "       [6.5, 3. , 5.8, 2.2],\n",
       "       [7.6, 3. , 6.6, 2.1],\n",
       "       [4.9, 2.5, 4.5, 1.7],\n",
       "       [7.3, 2.9, 6.3, 1.8],\n",
       "       [6.7, 2.5, 5.8, 1.8],\n",
       "       [7.2, 3.6, 6.1, 2.5],\n",
       "       [6.5, 3.2, 5.1, 2. ],\n",
       "       [6.4, 2.7, 5.3, 1.9],\n",
       "       [6.8, 3. , 5.5, 2.1],\n",
       "       [5.7, 2.5, 5. , 2. ],\n",
       "       [5.8, 2.8, 5.1, 2.4],\n",
       "       [6.4, 3.2, 5.3, 2.3],\n",
       "       [6.5, 3. , 5.5, 1.8],\n",
       "       [7.7, 3.8, 6.7, 2.2],\n",
       "       [7.7, 2.6, 6.9, 2.3],\n",
       "       [6. , 2.2, 5. , 1.5],\n",
       "       [6.9, 3.2, 5.7, 2.3],\n",
       "       [5.6, 2.8, 4.9, 2. ],\n",
       "       [7.7, 2.8, 6.7, 2. ],\n",
       "       [6.3, 2.7, 4.9, 1.8],\n",
       "       [6.7, 3.3, 5.7, 2.1],\n",
       "       [7.2, 3.2, 6. , 1.8],\n",
       "       [6.2, 2.8, 4.8, 1.8],\n",
       "       [6.1, 3. , 4.9, 1.8],\n",
       "       [6.4, 2.8, 5.6, 2.1],\n",
       "       [7.2, 3. , 5.8, 1.6],\n",
       "       [7.4, 2.8, 6.1, 1.9],\n",
       "       [7.9, 3.8, 6.4, 2. ],\n",
       "       [6.4, 2.8, 5.6, 2.2],\n",
       "       [6.3, 2.8, 5.1, 1.5],\n",
       "       [6.1, 2.6, 5.6, 1.4],\n",
       "       [7.7, 3. , 6.1, 2.3],\n",
       "       [6.3, 3.4, 5.6, 2.4],\n",
       "       [6.4, 3.1, 5.5, 1.8],\n",
       "       [6. , 3. , 4.8, 1.8],\n",
       "       [6.9, 3.1, 5.4, 2.1],\n",
       "       [6.7, 3.1, 5.6, 2.4],\n",
       "       [6.9, 3.1, 5.1, 2.3],\n",
       "       [5.8, 2.7, 5.1, 1.9],\n",
       "       [6.8, 3.2, 5.9, 2.3],\n",
       "       [6.7, 3.3, 5.7, 2.5],\n",
       "       [6.7, 3. , 5.2, 2.3],\n",
       "       [6.3, 2.5, 5. , 1.9],\n",
       "       [6.5, 3. , 5.2, 2. ],\n",
       "       [6.2, 3.4, 5.4, 2.3],\n",
       "       [5.9, 3. , 5.1, 1.8]])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150, 4)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5.1, 3.5, 1.4, 0.2],\n",
       "       [4.9, 3. , 1.4, 0.2],\n",
       "       [4.7, 3.2, 1.3, 0.2],\n",
       "       [4.6, 3.1, 1.5, 0.2],\n",
       "       [5. , 3.6, 1.4, 0.2]])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_features[:5,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5.1, 3.5],\n",
       "       [4.9, 3. ],\n",
       "       [4.7, 3.2],\n",
       "       [4.6, 3.1],\n",
       "       [5. , 3.6]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_features[0:5,0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['setosa', 'versicolor', 'virginica'], dtype='<U10')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_target_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150, 4)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150,)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_target.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 构建模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert iris_features.shape[0] == iris_target.shape[0]  #确保特征和标签对应的数据量都是150"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = tree.DecisionTreeClassifier(max_depth=4)\n",
    "clf = clf.fit(iris_features, iris_target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=4,\n",
       "            max_features=None, max_leaf_nodes=None,\n",
       "            min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "            min_samples_leaf=1, min_samples_split=2,\n",
       "            min_weight_fraction_leaf=0.0, presort=False, random_state=None,\n",
       "            splitter='best')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pydotplus\n",
    "from IPython.display import Image, display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dot_data = tree.export_graphviz(clf,\n",
    "                                out_file = None,\n",
    "                                feature_names = iris_feature_name,\n",
    "                                class_names = iris_target_name,\n",
    "                                filled=True,\n",
    "                                rounded=True\n",
    "                               )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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79u0BAGlpaSrlgwYNAvB0pcOzzyIqKgrR0dHQ1dWtkvGvX7+OwsJCZRxl0dHRQWBgIC5f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\nD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X1dhySEEKJgUlpXCCGEEKK0xMXF0a1bN6pVqyYldF9Arq6ubN++nQMHDjBhwgRdhyOE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\nIBAIBIKHiv8HeZWlrg9s2TsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph = pydotplus.graph_from_dot_data(dot_data)\n",
    "display(Image(graph.create_png()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 对整个训练集做预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.predict(iris_features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 对单个样本做预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "a1 = iris_features[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.predict(a1.reshape(1,-1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 对多个样本做预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "a1 = iris_features[1]\n",
    "a2 = iris_features[2]\n",
    "a3 = iris_features[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "b =np.row_stack((a1,a2,a3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.predict(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
